Console Output

Training and evaluating model for: Freezer
Dataset length: 34410 windows


 NILMModel(
  (conv1d): Conv1d(9, 9, kernel_size=(3,), stride=(1,), padding=(1,))
  (lstm): LSTM(9, 256, num_layers=5, batch_first=True, dropout=0.1)
  (dropout): Dropout(p=0.1, inplace=False)
  (relu): ReLU()
  (output_layer): Linear(in_features=256, out_features=1, bias=True)
)
Epoch [1/300], Train Loss: 0.005624
Validation Loss: 0.002883
Epoch [2/300], Train Loss: 0.002406
Validation Loss: 0.001994
Epoch [3/300], Train Loss: 0.002090
Validation Loss: 0.002346
Epoch [4/300], Train Loss: 0.001996
Validation Loss: 0.001786
Epoch [5/300], Train Loss: 0.001923
Validation Loss: 0.001751
Epoch [6/300], Train Loss: 0.001909
Validation Loss: 0.001579
Epoch [7/300], Train Loss: 0.001681
Validation Loss: 0.001593
Epoch [8/300], Train Loss: 0.001722
Validation Loss: 0.001513
Epoch [9/300], Train Loss: 0.001636
Validation Loss: 0.001492
Epoch [10/300], Train Loss: 0.001586
Validation Loss: 0.001440
Epoch [11/300], Train Loss: 0.001579
Validation Loss: 0.001426
Epoch [12/300], Train Loss: 0.001564
Validation Loss: 0.001442
Epoch [13/300], Train Loss: 0.001535
Validation Loss: 0.001393
Epoch [14/300], Train Loss: 0.001499
Validation Loss: 0.001427
Epoch [15/300], Train Loss: 0.001527
Validation Loss: 0.001467
Epoch [16/300], Train Loss: 0.001589
Validation Loss: 0.001419
Epoch [17/300], Train Loss: 0.001545
Validation Loss: 0.001417
Epoch [18/300], Train Loss: 0.001510
Validation Loss: 0.001366
Epoch [19/300], Train Loss: 0.001517
Validation Loss: 0.001380
Epoch [20/300], Train Loss: 0.001490
Validation Loss: 0.001424
Epoch [21/300], Train Loss: 0.001498
Validation Loss: 0.001365
Epoch [22/300], Train Loss: 0.001456
Validation Loss: 0.001334
Epoch [23/300], Train Loss: 0.001467
Validation Loss: 0.001371
Epoch [24/300], Train Loss: 0.001447
Validation Loss: 0.001322
Epoch [25/300], Train Loss: 0.001450
Validation Loss: 0.001306
Epoch [26/300], Train Loss: 0.001764
Validation Loss: 0.001518
Epoch [27/300], Train Loss: 0.001604
Validation Loss: 0.001453
Epoch [28/300], Train Loss: 0.001555
Validation Loss: 0.001413
Epoch [29/300], Train Loss: 0.001532
Validation Loss: 0.001480
Epoch [30/300], Train Loss: 0.001512
Validation Loss: 0.001389
Epoch [31/300], Train Loss: 0.001491
Validation Loss: 0.001366
Epoch [32/300], Train Loss: 0.001464
Validation Loss: 0.001356
Epoch [33/300], Train Loss: 0.001458
Validation Loss: 0.001334
Epoch [34/300], Train Loss: 0.001435
Validation Loss: 0.001347
Epoch [35/300], Train Loss: 0.001431
Validation Loss: 0.001310
Early stopping triggered

Evaluating model for: Freezer
Validation MAE: 31.669783 W
Validation MSE: 2152.109131 W²
Validation RMSE: 46.390831 W
Signal Aggregate Error (SAE): 0.002367
Normalized Disaggregation Error (NDE): 0.365487

      

Training and Validation Loss

Interactive Plot